Subgraph-Aware Joint Modeling for Graph Classification via Efficient Frequent Pattern Mining and Fusion

This paper proposes a subgraph-aware classification framework that integrates efficient frequent subgraph mining with graph neural networks (GNNs) to address the limitations of existing GNNs in capturing explicit local structures. Specifically,we first introduce an improved mining strategy to extrac...

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Autori principali:	Weiyao Xu, Yumeng Sun, Yumeng MA, Yu Cheng, Jie Liu, Yuan Sheng, Yiwei Zhang, Junliang Du
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2025-01-01
Serie:	IEEE Access
Soggetti:	Frequent subgraph mining graph neural network graph classification subgraph perception joint optimization
Accesso online:	https://ieeexplore.ieee.org/document/11141440/
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